11 papers
CAMMSR: Category-Guided Attentive Mixture of Experts for Multimodal Sequential Recommendation
Jinfeng Xu, Zheyu Chen, Shuo Yang +6
The explosion of multimedia data in information-rich environments has intensified the challenges of personalized content discovery, positioning recommendation systems as an essenti…
Learning and Editing Universal Graph Prompt Tuning via Reinforcement Learning
Jinfeng Xu, Zheyu Chen, Shuo Yang +4
Early graph prompt tuning approaches relied on task-specific designs for Graph Neural Networks (GNNs), limiting their adaptability across diverse pre-training strategies. In contra…
VI-MMRec: Similarity-Aware Training Cost-free Virtual User-Item Interactions for Multimodal Recommendation
Jinfeng Xu, Zheyu Chen, Shuo Yang +6
Although existing multimodal recommendation models have shown promising performance, their effectiveness continues to be limited by the pervasive data sparsity problem. This proble…
Multi-Cali Anything: Dense Feature Multi-Frame Structure-from-Motion for Large-Scale Camera Array Calibration
Jinjiang You, Hewei Wang, Yijie Li +8
Calibrating large-scale camera arrays, such as those in dome-based setups, is time-intensive and typically requires dedicated captures of known patterns. While extrinsics in such a…
MDVT: Enhancing Multimodal Recommendation with Model-Agnostic Multimodal-Driven Virtual Triplets
Jinfeng Xu, Zheyu Chen, Jinze Li +6
The data sparsity problem significantly hinders the performance of recommender systems, as traditional models rely on limited historical interactions to learn user preferences and…
Segregation and Context Aggregation Network for Real-time Cloud Segmentation
Yijie Li, Hewei Wang, Jiayi Zhang +5
Cloud segmentation from intensity images is a pivotal task in atmospheric science and computer vision, aiding weather forecasting and climate analysis. Ground-based sky/cloud segme…